Current solutions to solving the distributed information problem fall into two main classes: the client/server approach and the peer-to-peer approach. In a client/server system, there is generally a large powerful central server, usually a relational database, to which a set of clients talks in order to fetch, update, and query information. Such a network architecture can be viewed as a star with the clients forming the edges of the star and the large central server the center. The current state of the art in this field adds limited ability to distribute the central database to multiple server machines with perhaps the most sophisticated form being the “Information Warehouse” or “Corporate Information Factory” (CIF) approach described in the book “Corporate Information Factory” by W. H Inmon, Claudia Imhoff, and Ryan Sousa. Unfortunately, the CIF approach falls far short of what is necessary to handle more sophisticated systems such as those required for intelligence purposes, for example.
The peer-to-peer approach overcomes many of the limitations of the centralized system by allowing many machines on a network to cooperate as peers, however it does this by removing the concept of the specialized server, which limits its applicability in the area of intelligence systems, where the need for powerful distributed clusters of machines operating as a single logical ‘server’ for the purposes of processing an incoming ‘feed’ remains. Furthermore, neither approach addresses the needs of multimedia data and the consequent storage and ‘streaming’ demands that it places on the server architecture. Once the purpose of a system is broadened to acquisition of unstructured, non-tagged, time-variant, multimedia information (much of which is designed specifically to prevent easy capture and normalization by non-recipient systems), a totally different approach is required. In this arena, many entrenched notions of information science and database methodology must be discarded to permit the problem to be addressed. We shall call systems that attempt to address this level of problem, ‘Unconstrained Systems’ (UCS). An unconstrained system is one in which the source(s) of data have no explicit or implicit knowledge of, or interest in, facilitating the capture and subsequent processing of that data by the system.
What is needed, then, is an architecture that embodies concepts from both the client/server and the peer-to-peer approach, but which is modified to reflect the unique needs of a distributed multimedia intelligence system.